Field of the Invention
Embodiments of the present invention relate generally to computer vision and, more specifically, to model-based three-dimensional head pose estimation.
Description of the Related Art
Estimating the three-dimensional (3D) pose (i.e., the rotation and position) of the head of a user is an important technical problem that has many applications in facial motion capture, human-computer interaction, and video conferencing. For example, head pose estimation is a pre-requisite to gaze tracking, which has useful applications in cognitive science, automotive safety, and marketing research, to name a few. Additionally, head pose estimation is typically implemented in facial recognition and facial expression analysis.
Head pose estimation has traditionally been performed by capturing RGB images of a head of a user and analyzing the RGB images to identify facial features. For example, conventional head pose estimation techniques commonly implement rotation-specific classifiers that enable the pose of a head to be inferred by the shape, size, proportions, etc. of the facial features of a user. Alternatively, the RGB images may be registered to a 3D template associated with the face of the user.
However, conventional RGB-based head pose estimation techniques suffer from a number of drawbacks. In particular, RGB-based techniques typically produce unsatisfactory results when images are acquired in poor lighting conditions. For example, illumination variations, shadows, and occlusions may prevent accurate identification of the facial features of the user, leading to erroneous head pose estimation results. Additionally, RGB-based techniques typically require each user to initially perform a lengthy calibration sequence, through which the specific facial characteristics of each user are analyzed and stored via rotation-specific classifiers.
As the foregoing illustrates, more effective techniques for estimating the head pose of a user would be useful.